In recent years, many mobile phones and other mobile terminals are equipped with a positioning function such as a GPS (Global Positioning System). A user of a mobile terminal is thereby able to acquire one's current position information based on the positioning result of the mobile terminal, and receive various types of service information according to the user's current position by sending the positioning result, via a network, to the information distribution apparatus of the telecommunications carrier or the service provider.
Note that, as a technology of acquiring the user's position information, known is the method disclosed in PTL 1. The user position acquisition method disclosed in PTL 1 acquires the latitude-longitude coordinate position of the mobile phone through triangulation based on the transmission of multiple signals to the mobile phone, signal strength of multiple signals, differences in incoming time of different signals, differences in incoming angles of different signals, GPS signals, and their combinations.
Meanwhile, in order to effectively distribute service information according to the user's current position, it is necessary to distribute proper service information, which coincides with the user's preference, at an appropriate timing. In order to realize the above, it would be desirable to estimate the area that the user may likely visit in the future based on that user's past position information, and then distribute service information in light of the status of service being provided in that area, and that user's attributes such as age and gender.
As technologies for estimating the area that the user may likely visit in the future and distributing service information according to that area, conventionally, the technology disclosed in PTL 2 and the technology disclosed in PTL 3 have been proposed.
Specifically, the user position estimation method disclosed in PTL 2 estimates the user's future position by extracting the user's transit pattern between short-stay destinations, creating a transit model between short-stay destinations in which the frequency of transit pattern is associated with the transit pattern between short-stay destinations, and searching for a portable terminable that is taking a moving route that is similar to the moving route of other portable terminals based on the longest matching partial series length between past short-term/long-term stay time series data, and short-term/long-term stay time series data of other portable terminals.
Furthermore, the service information distribution method disclosed in PTL 3 estimates the traveling route from the current location to the destination based on data of past traveling routes of a vehicle, and distributes to the information providing apparatus mounted on the vehicle, or presents to the passenger of the vehicle, advertisement data around the estimated traveling route.